Optimized Approach (SPCA) for Load Balancing in Distributed HDFS Cluster

Hadoop is an open-source utility which allows users to provide massive input in terms of data and facilitates the computation. Role of Hadoop in load balancing is enormous which allows the user to configure the network of nodes having master/slave nodes. Hadoop’s typical architecture takes into cons...

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Vydáno v:SN computer science Ročník 1; číslo 2; s. 102
Hlavní autoři: Manjula, K., Meenakshi Sundaram, S.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Singapore Springer Nature Singapore 01.03.2020
Springer Nature B.V
Témata:
Advances in Computational Intelligence
Algorithms
Clusters
Commodities
Computer Imaging
Computer Science
Computer Systems Organization and Communication Networks
Configurations
Data Structures and Information Theory
Design
Distributed processing
Employment
FIFO
Homogeneity
Information Systems and Communication Service
Load balancing
Nodes
Original Research
Paradigms and Applications
Pattern Recognition and Graphics
Product reviews
Software Engineering/Programming and Operating Systems
User generated content
Vision
Work stations
Heterogeneous nodes
Load Balancing
Hadoop
ISSN:2662-995X, 2661-8907
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Shrnutí:Hadoop is an open-source utility which allows users to provide massive input in terms of data and facilitates the computation. Role of Hadoop in load balancing is enormous which allows the user to configure the network of nodes having master/slave nodes. Hadoop’s typical architecture takes into consideration the default configuration for the machine as homogeneous, but many of the real-time application or clusters of nodes will have the homogeneous configurations. Thus, an effort is made in this paper to consider the homogeneity of the nodes in clusters and build an efficient algorithm which does load balancing in an efficient way when compared with the default balancer of Hadoop which works well only on homogeneous nodes.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:2662-995X
2661-8907
DOI:10.1007/s42979-020-0107-8